Parabéns aos colaboradores do LAPISCO pelo artigo “Neurologist-level classification of stroke using a Structural Co-Occurrence Matrix based on the frequency domain” publicado no periódico Computers and Electrical Engineering (Elsevier). . Link de acesso gratuito por 50 dias: . https://authors.elsevier.com/a/1XYsBAQLrYTBRRead More →

Parabéns aos colaboradores do LAPISCO pelo artigo “Automatic histologically-closer classification of skin lesions” publicado no periódico Computerized Medical Imaging and Graphics (A2 em Ciência da Computação em em Eng. IV) Link/DOI do artigo: https://doi.org/10.1016/j.compmedimag.2018.05.004  Abstract: According to the American Cancer Society, melanoma is one of the most common types of cancer in the world. In 2017, approximately 87,110 new cases of skin cancer were diagnosed in the United States alone. A dermatoscope is a tool that captures lesion images with high resolution and is one of the main clinical tools to diagnose, evaluate and monitor this disease. This paper presents a new approach to classify melanoma automaticallyRead More →

Parabéns aos colaboradores do LAPISCO pelo artigo “A New Approach to Diagnose Parkinson’s Disease Using a Structural Cooccurrence Matrix for a Similarity Analysis” publicado no periódico   Computational Intelligence and Neuroscience Link/DOI do artigo: https://doi.org/10.1155/2018/7613282 Abstract: Parkinson’s disease affects millions of people around the world and consequently various approaches have emerged to help diagnose this disease, among which we can highlight handwriting exams. Extracting features from handwriting exams is an important contribution of the computational field for the diagnosis of this disease. In this paper, we propose an approach that measures the similarity between the exam template and the handwritten trace of the patient following the examRead More →